Simulation of Airflow in an Idealized Emphysematous Human Acinus
Bibliographic record
Abstract
Emphysema is the permanent enlargement of air spaces in the respiratory regions of the lung due to destruction of the inter-alveolar septa. The progressive coalescence of alveoli and alveolar ducts into larger airspaces leads to the disruption of normal airway wall motion and airflow rates within the pulmonary acinus. To contribute to the understanding of the individual effects of emphysema during its earliest stages, computational fluid dynamics (CFD) simulations of airflow in mathematically derived models of the pulmonary acinus were performed. The here generated computational domain consists of two generations of alveolar ducts within the pulmonary acinus, with alveolar geometries approximated as closely packed, 14-sided polygons. Physiologically realistic airflow rates and wall motions were used to study airflow patterns within subsequent generations of alveolar ducts during the inspiratory and expiratory phases of the breathing cycle. The effects of progressive emphysema on the airway wall motion and flow rates were simulated by sequentially removing all alveolar septa within each alveolar duct. Parametric studies were presented to independently assess the relative influence of progressive septal destruction of airway motion and flow rates. The results illustrate that septal destruction lowers the flow resistance through the alveolar ducts but has little influence on the mass transport of oxygen into the alveoli. Septal destruction has a net effect on the flow field by favoring the development of recirculatory flow patterns in individual alveoli.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".